Postdoctoral Fellow

Laplace Apply; United Kingdom; Hybrid; GBP 39,000 - 50,000; Full time

Job summary

Wellcome Sanger Institute in Hinxton invites applications for a Postdoctoral Fellow in Early-Life Genomics and Statistical Biology. The role focuses on early-life cohort genomics and molecular determinants of health, combining statistical genomics with computational analysis.

You will work with large linked datasets, develop reproducible workflows, and contribute to publications. A PhD in a quantitative life science plus strong coding in R or Python is required; hybrid work arrangements may

Qualifications

• A relevant PhD in genetics, statistics, computational biology, epidemiology or a related quantitative life science is required.
• Solid coding and statistical analysis skills.

Responsibilities

• Analyze large genomic and molecular datasets from early-life cohorts.
• Develop reproducible research workflows.
• Communicate results with collaborators.

Skills

Genomics

Proteomics

R

Python

Statistical analysis

Education

PhD in genetics, statistics, computational biology, epidemiology or related quantitative life science

Job description

Postdoctoral Fellow in Early-Life Genomics and Statistical Biology

United Kingdom

Apply by 10 Nov 2026

About This Opportunity

Wellcome Sanger Institute offers Postdoctoral Fellow in Early-Life Genomics and Statistical Biology in Hinxton, focused on early-life cohort genomics and molecular determinants of health.

The Wellcome Sanger Institute is recruiting a postdoctoral fellow to work on genomic and molecular evidence from early-life or population cohorts, within a research programme associated with the Martin group. The project aims to understand variation in health-related traits using large, linked biological datasets. The work integrates statistical genomics and computational analysis with cohort-specific measurements, potentially including genetic variation, proteomic signals and cell-free molecular data. The role involves analysis of large datasets, reproducible research workflows and communication of results with collaborators. A relevant PhD in genetics, statistics, computational biology, epidemiology or a related quantitative life science is required, together with solid coding and statistical analysis skills. Compensation or funding: GBP 38,570-49,893 per year. Stated appointment or programme length: Three years. Application timing: 10 November 2026 at 23:59 GMT listed by AcademicPositions. Who This Opportunity Is Best Suited For: Applicants experienced with R or Python, large cohort datasets, statistical inference and biological interpretation of molecular measurements may be especially suitable. Potential Challenges / Who May Find It Less Suitable: The project requires careful handling of potentially complex and restricted human cohort data; it is not an entry-level wet-lab training position. Verify specific conditions for hybrid work directly with the employer. Overall Opportunity Assessment: The research combines population-scale data and early-life molecular biology to address the origins of human traits or disease risk.

Early-life cohort genomics and molecular determinants of health

Level Postdoc

Time Commitment Full-time

Duration Three years

Reference Code JR104058

Field Statistical Genomics

Specialization Biomedical Sciences

Organization Type Research Institute

Funding & Compensation

Amount GBP 38,570-49,893 / Per Year

Funding Type Salary

Funding Status Paid

Period Per Year

Requirements

Education

A relevant PhD in genetics, statistics, computational biology, epidemiology or a related quantitative life science is required, together with solid coding and statistical analysis skills.

Experience

Technical Skills Genomics Proteomics R Python Statistical analysis